空間旋轉(zhuǎn)目標(biāo)窄帶雷達(dá)干涉式三維成像與微動(dòng)特征提取

胡健; 羅迎; 張群; 康樂(lè); 何其芳

doi:10.11999/JEIT180372

空間旋轉(zhuǎn)目標(biāo)窄帶雷達(dá)干涉式三維成像與微動(dòng)特征提取

doi: 10.11999/JEIT180372

胡健^{1, 2, ,},
羅迎^{1, 3, 4},
張群^{1, 3, 4},
康樂(lè)^{1, 3},
何其芳^{1, 5}

1.
空軍工程大學(xué)信息與導(dǎo)航學(xué)院 ??西安 ??710077
2.
95633部隊(duì) ??邛崍 ??611531
3.
信息感知技術(shù)協(xié)同創(chuàng)新中心 ??西安 ??710077
4.
復(fù)旦大學(xué)電磁波信息科學(xué)教育部重點(diǎn)實(shí)驗(yàn)室 ??上海 ??200433
5.
93534部隊(duì) ??天津 ??301700

基金項(xiàng)目: 國(guó)家自然科學(xué)基金項(xiàng)目(61571457, 61471386)，陜西省青年科技新星計(jì)劃項(xiàng)目(2016KJXX-49)

詳細(xì)信息

作者簡(jiǎn)介:
胡?。耗?，1986年生，博士生，研究方向?yàn)槔走_(dá)成像與雷達(dá)目標(biāo)微多普勒效應(yīng)

羅迎：男，1984年生，副教授，博士生導(dǎo)師，研究方向?yàn)槔走_(dá)成像與目標(biāo)識(shí)別、雷達(dá)目標(biāo)微多普勒效應(yīng)、認(rèn)知雷達(dá)

張群：男，1964年生，教授，博士生導(dǎo)師，研究方向?yàn)槔走_(dá)成像、目標(biāo)識(shí)別與電子對(duì)抗

康樂(lè)：男，1993年生，博士生，研究方向?yàn)槔走_(dá)成像與目標(biāo)識(shí)別

何其芳：女，1993年生，助理工程師，研究方向?yàn)槔走_(dá)信號(hào)處理與目標(biāo)識(shí)別

通訊作者:
胡健　hujianinstar@163.com

中圖分類(lèi)號(hào): TN957.52
計(jì)量
- 文章訪問(wèn)數(shù): 2098
- HTML全文瀏覽量: 712
- PDF下載量: 94
- 被引次數(shù): 0
出版歷程
- 收稿日期: 2018-04-23
- 修回日期: 2018-11-01
- 網(wǎng)絡(luò)出版日期: 2018-11-12
- 刊出日期: 2019-02-01

Three-dimensional Interferometric Imaging and Micro-motion Feature Extraction of Rotating Space Targets Based on Narrowband Radar

Jian HU^{1, 2
, ,},
Ying LUO^{1, 3, 4},
Qun ZHANG^{1, 3, 4},
Le KANG^{1, 3},
Qifang He^{1, 5}

1.
Institute of Information and Navigation, Air Force Engineering University, Xi’an 710077, China
2.
95633 PLA Troop, Qionglai 611531, China
3.
Collaborative Innovation Center of Information Sensing and Understanding, Xi’an 710077, China
4.
Key Laboratory for Information Science of Electromagnetic Waves (Ministry of Education), Fudan University, Shanghai 200433, China
5.
93534 PLA Troop, Tianjin 301700, China

Funds: The National Natural Science Foundation of China (61571457, 61471386), The Youth Science and Technology Nova Program of Shaanxi Province (2016KJXX-49)

摘要

摘要:
該文根據(jù)干涉式逆合成孔徑雷達(dá)(InISAR)中多天線干涉處理的思想，提出一種基于L型3天線模型的空間旋轉(zhuǎn)目標(biāo)3維成像與3維微動(dòng)特征提取方法。將微多普勒效應(yīng)理論與多天線干涉處理技術(shù)相結(jié)合，在時(shí)頻面上通過(guò)Viterbi算法分離散射點(diǎn)并進(jìn)行干涉處理獲取目標(biāo)在各時(shí)刻沿基線方向的2維投影坐標(biāo)；根據(jù)目標(biāo)微動(dòng)特性，采用非迭代橢圓擬合方法重構(gòu)出散射點(diǎn)的高度維信息，實(shí)現(xiàn)目標(biāo)的真實(shí)3維成像，并在成像過(guò)程中提取目標(biāo)的3維微動(dòng)特征參數(shù)。仿真實(shí)驗(yàn)驗(yàn)證了所提方法的有效性與魯棒性。
- 窄帶雷達(dá) /
- 干涉式3維成像 /
- 空間目標(biāo) /
- 微動(dòng)特征提取
Abstract:
Inspired by the idea of multi-antenna interferometric processing in Interferometric Inverse Synthetic Aperture Radar (InISAR), by utilizing an L-shaped three-antenna imaging model, a Three-Dimensional (3-D) interferometric imaging and micro-motion feature extraction method for rotating space targets is proposed. Based on the integration of micro-Doppler (m-D) effect theory and multi-antenna interferometry processing technology, the m-D curves corresponding to different scatterers are obtained on the time-frequency plane and separated via Viterbi algorithm effectively, and then the projected coordinates of scatterers along the direction of baselines are reconstructed by interferometric processing. The height information of scatterers is solved by ellipse fitting, and 3-D imaging for the rotating space target is realized. Meanwhile, some 3-D micro-motion features are exactly extracted during imaging. Simulation results validate the effectiveness and the robustness of the method.
- Narrowband radar /
- 3-D interferometric imaging /
- Space target /
- Micro-motion feature extraction

HTML全文

圖 1 目標(biāo)與雷達(dá)之間的幾何關(guān)系示意圖

下載: 全尺寸圖片幻燈片

圖 2 窄帶雷達(dá)中自旋目標(biāo)微多普勒信號(hào)分析示意圖

下載: 全尺寸圖片幻燈片

圖 3 散射點(diǎn)旋轉(zhuǎn)軌跡及其在X-Z平面上投影的對(duì)應(yīng)關(guān)系

下載: 全尺寸圖片幻燈片

圖 4 3維干涉成像仿真結(jié)果

下載: 全尺寸圖片幻燈片

圖 5 ${\rm{SNR}} =5 \; {\rm{dB}}$時(shí)的3維干涉成像仿真結(jié)果

下載: 全尺寸圖片幻燈片

圖 6 不同信噪比下的微動(dòng)特征提取絕對(duì)誤差

下載: 全尺寸圖片幻燈片

表 1 3維微動(dòng)特征提取結(jié)果與估計(jì)誤差

參數(shù)	${M_{a1}}$ (Hz)	${M_{a2}}$ (Hz)	${\varOmega _r}$ (rad/s)	${r_1}$ (m)	${r_2}$ (m)	${{{ω}}_r}$ (rad/s)
理論值	546.3059	182.1020	10.8828	3.6742	1.5000	[6.6908, –8.5830, –0.0121]
估計(jì)值	546.2000	182.4000	10.8900	3.6786	1.4166	[6.6980, –8.5774, –0.0151]
絕對(duì)誤差	0.1059	0.2980	0.0072	0.0044	0.0834	0.0287

下載: 導(dǎo)出CSV

參考文獻(xiàn)(12)

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